均值模糊与高斯模糊

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>
using namespace cv;
using namespace std;


const int g_nTrackbarMaxValue = 9;     //定义轨迹条最大值
int g_nTrackbarValue;                   //定义轨迹条初始值
int g_nKernelValue;                     //定义kernel尺寸
Mat src, dst;

//均值滤波
void on_kernelTrackbar(int,void *)
{
    //根据输入值重新计算kernel尺寸
    g_nKernelValue = g_nTrackbarValue * 2 + 1;

    //均值滤波函数
    blur(src, dst, Size(g_nKernelValue, g_nKernelValue));

    imshow("均值滤波", dst);
}

//高斯滤波
void on_kernelTrackbar2(int, void*)
{
    //根据输入值重新计算kernel尺寸
    g_nKernelValue = g_nTrackbarValue * 2 + 1;

    //均值滤波函数
    GaussianBlur(src, dst, Size(g_nKernelValue, g_nKernelValue),11,11);

    imshow("均值滤波", dst);
}

int main()
{
    
    //原图
    src = imread(".//pic//kate.png",IMREAD_UNCHANGED);
    
    if (!src.data)
    {
        cout << "load error" << endl;
        return -1;
    }
    

    namedWindow("均值滤波", WINDOW_AUTOSIZE);   //定义滤波后图像显示窗口属性
    //定义轨迹条名称和最大值
    char kernelName[20];
    sprintf(kernelName, "kernel尺寸 %d", g_nTrackbarMaxValue);

    //创建轨迹条
    createTrackbar(kernelName, "均值滤波", &g_nTrackbarValue, g_nTrackbarMaxValue, on_kernelTrackbar2);
    on_kernelTrackbar(g_nTrackbarValue, 0);


    waitKey(0);
    return 0;
}